Local vasodilation in response to hypoxia is a fundamental physiologic response ensuring oxygen delivery to tissues under metabolic stress. Recent studies identify a role for the red blood cell (RBC), with hemoglobin the hypoxic sensor. Herein, we investigate the mechanisms regulating this process and explore the relative roles of adenosine triphosphate, S-nitrosohemoglobin, and nitrite as effectors. We provide evidence that hypoxic RBCs mediate vasodilation by reducing nitrite to nitric oxide (NO) and ATP release. NO dependence for nitrite-mediated vasodilation was evidenced by NO gas formation, stimulation of cGMP production, and inhibition of mitochondrial respiration in a process sensitive to the NO scavenger C-PTIO. The nitrite reductase activity of hemoglobin is modulated by heme deoxygenation and heme redox potential, with maximal activity observed at 50% hemoglobin oxygenation (P 50 ). Concomitantly, vasodilation is initiated at the P 50 , suggesting that oxygen sensing by hemoglobin is mechanistically linked to nitrite reduction and stimulation of vasodilation. Mutation of the conserved ␤93cys residue decreases the heme redox potential (ie, decreases E 1/2 ), an effect that increases nitrite reductase activity and vasodilation at any given hemoglobin saturation. These data support a function for RBC hemoglobin as an allosterically and redox-regulated nitrite reductase whose "enzyme activity" couples hypoxia to increased NO-dependent blood flow. (Blood. 2006;107:566-574)

Neuroglobin is a highly conserved hemoprotein of uncertain physiological function that evolved from a common ancestor to hemoglobin and myoglobin. It possesses a six-coordinate heme geometry with proximal and distal histidines directly bound to the heme iron, although coordination of the sixth ligand is reversible. We show that deoxygenated human neuroglobin reacts with nitrite to form nitric oxide (NO). This reaction is regulated by redox-sensitive surface thiols, cysteine 55 and 46, which regulate the fraction of the five-coordinated heme, nitrite binding, and NO formation. Replacement of the distal histidine by leucine or glutamine leads to a stable five-coordinated geometry; these neuroglobin mutants reduce nitrite to NO ϳ2000 times faster than the wild type, whereas mutation of either Cys-55 or Cys-46 to alanine stabilizes the six-coordinate structure and slows the reaction. Using lentivirus expression systems, we show that the nitrite reductase activity of neuroglobin inhibits cellular respiration via NO binding to cytochrome c oxidase and confirm that the six-to-five-coordinate status of neuroglobin regulates intracellular hypoxic NO-signaling pathways. These studies suggest that neuroglobin may function as a physiological oxidative stress sensor and a post-translationally redox-regulated nitrite reductase that generates NO under six-tofive-coordinate heme pocket control. We hypothesize that the sixcoordinate heme globin superfamily may subserve a function as primordial hypoxic and redox-regulated NO-signaling proteins.

Purpose: To enable accurate MR parameter mapping with accelerated data acquisition, utilizing recent advances in constrained imaging with sparse sampling. Theory and Methods: A new constrained reconstruction method based on low-rank and sparsity constraints is proposed to accelerate MR parameter mapping. More specifically, the proposed method simultaneously imposes low-rank and joint sparse structures on contrast-weighted image sequences within a unified mathematical formulation. With a pre-estimated subspace, this formulation results in a convex optimization problem, which is solved using an efficient numerical algorithm based on the alternating direction method of multipliers. Results: To evaluate the performance of the proposed method, two application examples were considered: i) T2 mapping of the human brain, and ii) T1 mapping of the rat brain. For each application, the proposed method was evaluated at both moderate and high acceleration levels. Additionally, the proposed method was compared with two state-of-the-art methods that only use a single low-rank or joint sparsity constraint. The results demonstrate that the proposed method can achieve accurate parameter estimation with both moderately and highly undersampled data. Although all methods performed fairly well with moderately undersampled data, the proposed method achieved much better performance (e.g., more accurate parameter values) than the other two methods with highly undersampled data. Conclusions: Simultaneously imposing low-rank and sparsity constraints can effectively improve the accuracy of fast MR parameter mapping with sparse sampling.

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